3 Introduction Background: Our Intention:Although there is an abundance of models for health care processes, few consider multiple units or departments. – Jun et al. 1999Our Intention:What relationships were being accounted for? (i.e. What areas of the hospital?)How were they being modelled?(i.e. What techniques?)Identify examples of multi-department models.What factors are holding modellers back?

4 Search Method Other papers found via citationsJun, J., Jacobson, S., and Swisher, J. (1999). Application of Discrete-Event Simulation in Health Care Clinics: A Survey. Journal of the Operational Research Society, 50(2):109–123.Cited by over 70 papers21.4% Tutorial or Instructional10% Surveys40% Applications / Case Studies of a Single Department28.6% Applications / Case Studies of a Multiple DepartmentOther papers found via citationsIn Total: Identified 78 papers which we considered to be of “Multiple Department”

5 What relationships were being accounted for. (i. eWhat relationships were being accounted for? (i.e. What areas of the hospital?)How were they being modelled?(i.e. What techniques?)Identify examples of multi-department models.What factors are holding modellers back?

6 What relationships were being accounted for. (i. eWhat relationships were being accounted for? (i.e. What areas of the hospital?)

19 Notable ReferencesBrailsford, S. et al (2004). Emergency and on-demand health care: modelling a large complex system. Journal of the Operational Research Society, 55(1):34– 42.Scope: Referral, Ambulances, ED, Lab/DI, ICU, WardTechnique: Systems DynamicsDexter, F. (2009). Bibliography of Operating Room Management Articles. Retrieved October 10,2008 fromScope: Surgical ServicesSystem dynamics is an approach to understanding the behaviour of complex systems over time. It deals with internal feedback loops and time delays that affect the behaviour of the entire system.[1] What makes using system dynamics different from other approaches to studying complex systems is the use of feedback loops and stocks and flows. These elements help describe how even seemingly simple systems display baffling nonlinearity.

20 Belien, J., et al. (2006). Visualizing the Demand for Various Resources as a Function of the Master Surgery Schedule: A Case Study. Journal of Medical Systems, 30(5):343–350.Scope: OR, Lab/DITechnique: SoftwareCochran, J. and Bharti, A. (2006a). A multi-stage stochastic methodology for whole hospital bed planning under peak loading. International Journal of Industrial and Systems Engineering, 1(1):8–36.Scope: OR, ICU, WardTechnique: Queueing Theory & SimulationSystem dynamics is an approach to understanding the behaviour of complex systems over time. It deals with internal feedback loops and time delays that affect the behaviour of the entire system.[1] What makes using system dynamics different from other approaches to studying complex systems is the use of feedback loops and stocks and flows. These elements help describe how even seemingly simple systems display baffling nonlinearity.

21 Fletcher, A. and Worthington, D. (2007)Fletcher, A. and Worthington, D. (2007). What is a ‘generic’ hospital model? Retrieved October 13, 2008:System dynamics is an approach to understanding the behaviour of complex systems over time. It deals with internal feedback loops and time delays that affect the behaviour of the entire system.[1] What makes using system dynamics different from other approaches to studying complex systems is the use of feedback loops and stocks and flows. These elements help describe how even seemingly simple systems display baffling nonlinearity.

24 Problem 1: Ambiguous Care Paths“patient care plans for the individual patient are rarely formally recorded, as such, they tend to evolve with the patient stay, and exist in a piece-meal fashion in the minds of physicians, nurses, and discharge planners” (Kopach-Konrad et al., 2007).

26 Problem 2: Complexity & VariabilityThe complexity and variability that is inherent in health care either greatly limits the scope of models or forces modellers to take a more macro view.Either way, researchers loose a certain amount of perspective and perhaps draw conclusions on a model that does not incorporate the entire set of circumstances

27 Coping with: Complexity & Variabilitydistinguish between those complicating factors that have the greatest influence and those factors which are simply attributes.To limit the amount of variability time should initially be spent eliminating the variability caused by the system itself.good protocols or work practicesa clear understanding of the patient care trajectories.

28 Problem 3: Hospital Culture“management does not consider the total care chain from admission to discharge, but mainly focuses on the performance of individual units. Not surprisingly, this has often resulted in diminished patient access without any significant reduction in costs” (de Bruin et al., 2005).People working in the health care system are very knowledgeable about their own area but have relatively little understanding of what goes on in the next department. (Carter 2002)

29 Coping with: Hospital CultureFrom an Operational Research Perspective:Better ModelsLarger Scopes with a more sophisticated understanding of the requirements of the environmentPractically RelevantResults which illustrate the benefits of coordination between departments

31 ORchestra BibliographyA comprehensive overview of scientific literature in the field of “Operations Research in Health Care”Can be accessed at:Is maintained by the Center for Health Care Operations Improvement and Research (CHOIR)